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This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading.

We present a case study of how rumors spread on Twitter during a recent disaster situation, the Great East Japan earthquake of March 11, 2011, based on comparison to a normal situation. We specifically examine rumor disaffirmation because automatic rumor extraction is difficult. Extracting rumor-disaffirmation is easier than extracting the rumors themselves. We classify tweets in disaster situations, analyze tweets in disaster situations based on users' impressions and compare the spread of rumor tweets in a disaster situation to that in a normal situation.

The analysis results showed the following characteristics of rumors in a disaster situation. The information transmission is 74.9 per cent, representing the greatest number of tweets in our data set. Rumor tweets give users strong behavioral facilitation, make them feel negative and foment disorder. Rumors of a normal situation spread through many hierarchies but the rumors of disaster situations are two or three hierarchies, which means that the rumor spreading style differs in disaster situations and in normal situations.

The originality of this paper is to target rumors on Twitter and to analyze rumor characteristics by multiple aspects using not only rumor-tweets but also disaffirmation-tweets as an investigation object.

This paper aims to investigate the impacts of rumors' information characteristics on people's believing and spreading of rumors online.

This study employed a mixed-methods approach by combining qualitative and quantitative methods. In study 1, the authors explored different types of rumors and their information source characteristics through qualitative research. In study 2, the authors utilized the findings from study 1 to develop an empirical model to verify the impact of these characteristics on the public's behaviors of believing and spreading rumors by content analysis and quantitative research.

The results show that five information source characteristics – credibility, professionalism, attractiveness, mystery and concreteness – influence the spreading effect of different types of rumors.

This study contributes to rumor spreading research by deepening the theory of information source characteristics and adding to the emerging literature on the COVID-19 pandemic.

Insights from this research offer important practical implications for policymakers and online-platform operators by highlighting how to suppress the spread of rumors, particularly those associated with COVID-19.

This research introduces the theory of information source characteristics into the field of rumor spreading and adopts a mixed-methods approach, taking COVID-19 rumors as a typical case, which provides a unique perspective for a deeper understanding of rumor spreading's antecedences.

This paper aims to investigate the impact of product release on word of mouth (WOM) behavior within and across rival online brand communities for technology products and evaluate competing predictions made by social identity theory and the group problem solving perspective of rumors.

In Study 1, 72,749 messages posted by 5,777 users over a 13-month period on two rival online brand forums were content analyzed using linguistic inquiry and word count, a linguistic content analysis program. In Study 2, two experiments were conducted to verify the theoretical explanation offered.

Marked differences were found as WOM transitioned from pre-release rumor to post-release facts. Prior to release, brand loyalists show an increased willingness to spread positive WOM about rival brands’ products. However, this willingness dissipated upon product release. This is in noted contrast to predictions made for experience goods.

This study examines the uncertainty generated by a rival brand’s upcoming new product within a brand community. While centered on a technologically oriented consumer group, this study addresses a longstanding theoretical conundrum and provides interesting areas for future research.

Surprisingly, it is the most active and ostensibly loyal brand supporters who spread pre-release rumors about rival brands. Managers should not assume that “loyalists” will not seriously discuss the potential offerings of rival brands. Product rumors thus present rival marketers with a unique “move it or lose it” opportunity to spread positive buzz among rival brand loyalists. However, this window of opportunity closes rapidly upon product release.

This is the first paper to examine the nature of new product rumors at this scale, including both pre- and post-release WOM.

Social media rumor combating is a global concern in academia and industry. Existing studies lack a clear definition and overall conceptual framework of users' rumor-combating behaviors. Therefore, this study attempts to empirically derive a typology of rumor-combating behaviors of social media users.

A three-phase typology development approach is adopted, including content analysis, multidimensional scaling (MDS), interpreting and labeling. Qualitative and quantitative data collection and analysis methods are employed.

The elicited 40 rumor-combating behaviors vary along two dimensions: high versus low difficulty of realization, and low versus high cognitive load. Based on the two dimensions, the 40 behaviors are further divided into four categories: rumor-questioning behavior, rumor-debunking behavior, proactive-appealing behavior, and literacy enhancement behavior.

This typology will serve as reference for social media platforms and governments to further explore the interventions to encourage social media users to counter rumor spreading based on various situations and different characteristics of rumor-combating behaviors.

This study provides a typology of rumor-combating behaviors from a novel perspective of user participation. The typology delves into the conceptual connotations and basic forms of rumor combating, allowing for a comprehensive understanding of the complete spectrum of users' rumor-combating behaviors. Furthermore, the typology identifies the similarities and the differences between various rumor-combating behaviors, thus providing implications and directions for future research on rumor-combating behaviors.

With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.

Employees often engage in informal interpersonal communication within organizations. Such communication is essential for creating a better work environment. While there are documented advantages of such communication, often, such communication is plagued by rumors. The purpose of this paper is to highlight the menace posed by rumors, the motivations for employees to engage in rumormongering, and possible ways to manage the spread of these rumors.

The paper draws from published literature on rumor research to illustrate the menace of rumors within organizational contexts, motivation to engage in rumormongering, and possible management strategies.

The paper identifies the menace of rumors in organizations, illustrates the reasons why employees share rumors, and discusses the possible methods to manage the spread of rumors.

Rumor propagation in organizations is an extremely dynamic process. The key element in rumor management is the swiftness and agility in intervention and management of rumors using strategies described in this paper. HR managers can monitor conversations to identify potentially harmful rumors and tackle this menace.

When the spread of online health rumors on social media causes public concerns, the public is calling for action. However, little study has investigated how Facebook reaction icons (expressing feelings function) affect online users' behavioral intentions (intention to trust and share) toward online health rumor posts. The current study addresses this gap by focusing on the effect of Facebook reaction icons in two conditions: Facebook reaction icons' presence (versus absence), and Facebook reaction icons' emotional valence (positive versus negative versus neutral). Moreover, the authors also investigated the interaction between Facebook reaction icons' emotional valence and online health rumor posts' framing headlines (gain versus loss).

The authors used a 7 (Facebook reaction icons: Love, Like, Haha, Wow, Sad, Angry and no icon) × 2 (Facebook framing headlines: gain and loss) between-subjects design, analyzing 507 samples from online users with one-way ANOVA and MANOVA.

Results show that online health rumor posts without Facebook reaction icons are more likely to negatively change online users' behavioral intentions than the posts with Facebook reaction icons; negative reaction icons (Sad and Angry) lower online users' behavioral intentions than positive reaction icons (Love and Like). Further, the incongruency effect of interaction (i.e. positive reaction icons with a negative message) would have more negative effects on online users' behavioral intentions than the congruency effect (i.e. positive reaction icons with a positive message).

This study has rich contributions to theoretical and practical implications for the Facebook platform and Facebook users to apply Facebook reaction icons against online health rumor posts.

Technology has eased access to information. During the ongoing COVID-19 pandemic, ease of access and transmission of information via social media has led to ambiguity, misinformation and uncertainty. This research studies the aforementioned behaviours of information sharing and verification related to COVID-19, in the context of social media.

Two studies have been carried out. Study 1, with Indian social media users, is a two-factor between-subjects experimental design that investigated the effect of message polarity (positive versus negative) and message type (news versus rumour) on the dissemination and verification behaviour of COVID-19-related messages. The study also investigated the mediation of perceived message importance and health anxiety. Study 2 is a replica study conducted with US users.

The study finding revealed significantly higher message sharing for news than rumour. Further, for the Indian users, message with positive polarity led to higher message sharing and message with negative polarity led to higher verification behaviour. On the contrary, for the US users, message with negative polarity led to higher message sharing and message with positive polarity led to higher verification behaviour. Finally, the study revealed message importance mediates the relationship of message type and message sharing behaviour for Indian and US users; however, health anxiety mediation was significant only for Indian users.

The findings offer important implications related to information regulation during a health crisis. Unverified information sharing is harmful during a pandemic. The study sheds light on this behaviour such that stakeholders get insights and better manage the information being disseminated.

The study investigates the behaviour of sharing and verification of social media messages between users containing health information (news and rumour) related to the ongoing COVID-19 pandemic.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2020-0282

The purpose of the study is to understand how socially shared misinformation and rumors can enhance the motivation to protect personal interests and enhance social practices of panic buying.

The study employed a number of qualitative data collection methods for the purpose of triangulation, as it can offer thick interpretation and can help to develop a context specific research framework.

The shared misinformation and rumors on social media developed into psychological, physical and social threats; therefore, people started panic buying to avoid these negative consequences. People believed that there were differences between the information shared by politicians and government officials and reality, such as “everything is under control,” whereas social media showed people standing in long queues and struggling to buy the necessities of life. The shared misinformation and rumors on social media became viral and received social validation, which created panic buying in many countries.

It is the responsibility of government, politicians, leaders, media and the public to control misinformation and rumors, as many people were unable to buy groceries due either to socio-economic status or their decisions of late buying, which increased depression among people.

The study merged the theory of rumor (TORT) transmission and protection motivation theory (PMT) to understand how misinformation and rumors shared through social media increased global uncertainty and the desire to panic buy across the world.

The spread of rumors on social media has caused increasing concerns about an under-informed or even misinformed public when it comes to scientific issues. However, researchers have rarely investigated their diffusion in non-western contexts. This study aims to systematically examine the content and network structure of rumor-related discussions around genetically modified organisms (GMOs) on Chinese social media.

This study identified 21,837 rumor-related posts of GMOs on Weibo, one of China's most popular social media platforms. An approach combining social network analysis and content analysis was employed to classify user attitudes toward rumors, measure the level of homophily of their attitudes and examine the nature of their interactions.

Though a certain level of homophily existed in the interaction networks, referring to the observed echo chamber effect, Weibo also served as a public forum for GMO discussions in which cross-cutting ties between communities existed. A considerable amount of interactions emerged between the pro- and anti-GMO camps, and most of them involved providing or requesting information, which could mitigate the likelihood of opinion polarization. Moreover, this study revealed the declining role of traditional opinion leaders and pointed toward the need for alternative strategies for efficient fact-checking.

In general, the findings of this study suggested that microblogging platforms such as Weibo can function as public forums for discussing GMOs that expose users to ideologically cross-cutting viewpoints. This study stands to provide important insights into the viral processes of scientific rumors on social media.